api_op_CreateMLEndpoint.go

// Code generated by smithy-go-codegen DO NOT EDIT.

package neptunedata

import (
	"context"
	"fmt"
	awsmiddleware "github.com/aws/aws-sdk-go-v2/aws/middleware"
	"github.com/aws/smithy-go/middleware"
	smithyhttp "github.com/aws/smithy-go/transport/http"
)

// Creates a new Neptune ML inference endpoint that lets you query one specific
// model that the model-training process constructed. See Managing inference
// endpoints using the endpoints command (https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-endpoints.html)
// . When invoking this operation in a Neptune cluster that has IAM authentication
// enabled, the IAM user or role making the request must have a policy attached
// that allows the neptune-db:CreateMLEndpoint (https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#createmlendpoint)
// IAM action in that cluster.
func (c *Client) CreateMLEndpoint(ctx context.Context, params *CreateMLEndpointInput, optFns ...func(*Options)) (*CreateMLEndpointOutput, error) {
	if params == nil {
		params = &CreateMLEndpointInput{}
	}

	result, metadata, err := c.invokeOperation(ctx, "CreateMLEndpoint", params, optFns, c.addOperationCreateMLEndpointMiddlewares)
	if err != nil {
		return nil, err
	}

	out := result.(*CreateMLEndpointOutput)
	out.ResultMetadata = metadata
	return out, nil
}

type CreateMLEndpointInput struct {

	// A unique identifier for the new inference endpoint. The default is an
	// autogenerated timestamped name.
	Id *string

	// The minimum number of Amazon EC2 instances to deploy to an endpoint for
	// prediction. The default is 1
	InstanceCount *int32

	// The type of Neptune ML instance to use for online servicing. The default is
	// ml.m5.xlarge . Choosing the ML instance for an inference endpoint depends on the
	// task type, the graph size, and your budget.
	InstanceType *string

	// The job Id of the completed model-training job that has created the model that
	// the inference endpoint will point to. You must supply either the
	// mlModelTrainingJobId or the mlModelTransformJobId .
	MlModelTrainingJobId *string

	// The job Id of the completed model-transform job. You must supply either the
	// mlModelTrainingJobId or the mlModelTransformJobId .
	MlModelTransformJobId *string

	// Model type for training. By default the Neptune ML model is automatically based
	// on the modelType used in data processing, but you can specify a different model
	// type here. The default is rgcn for heterogeneous graphs and kge for knowledge
	// graphs. The only valid value for heterogeneous graphs is rgcn . Valid values for
	// knowledge graphs are: kge , transe , distmult , and rotate .
	ModelName *string

	// The ARN of an IAM role providing Neptune access to SageMaker and Amazon S3
	// resources. This must be listed in your DB cluster parameter group or an error
	// will be thrown.
	NeptuneIamRoleArn *string

	// If set to true , update indicates that this is an update request. The default
	// is false . You must supply either the mlModelTrainingJobId or the
	// mlModelTransformJobId .
	Update *bool

	// The Amazon Key Management Service (Amazon KMS) key that SageMaker uses to
	// encrypt data on the storage volume attached to the ML compute instances that run
	// the training job. The default is None.
	VolumeEncryptionKMSKey *string

	noSmithyDocumentSerde
}

type CreateMLEndpointOutput struct {

	// The ARN for the new inference endpoint.
	Arn *string

	// The endpoint creation time, in milliseconds.
	CreationTimeInMillis *int64

	// The unique ID of the new inference endpoint.
	Id *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata

	noSmithyDocumentSerde
}

func (c *Client) addOperationCreateMLEndpointMiddlewares(stack *middleware.Stack, options Options) (err error) {
	if err := stack.Serialize.Add(&setOperationInputMiddleware{}, middleware.After); err != nil {
		return err
	}
	err = stack.Serialize.Add(&awsRestjson1_serializeOpCreateMLEndpoint{}, middleware.After)
	if err != nil {
		return err
	}
	err = stack.Deserialize.Add(&awsRestjson1_deserializeOpCreateMLEndpoint{}, middleware.After)
	if err != nil {
		return err
	}
	if err := addProtocolFinalizerMiddlewares(stack, options, "CreateMLEndpoint"); err != nil {
		return fmt.Errorf("add protocol finalizers: %v", err)
	}

	if err = addlegacyEndpointContextSetter(stack, options); err != nil {
		return err
	}
	if err = addSetLoggerMiddleware(stack, options); err != nil {
		return err
	}
	if err = addClientRequestID(stack); err != nil {
		return err
	}
	if err = addComputeContentLength(stack); err != nil {
		return err
	}
	if err = addResolveEndpointMiddleware(stack, options); err != nil {
		return err
	}
	if err = addComputePayloadSHA256(stack); err != nil {
		return err
	}
	if err = addRetry(stack, options); err != nil {
		return err
	}
	if err = addRawResponseToMetadata(stack); err != nil {
		return err
	}
	if err = addRecordResponseTiming(stack); err != nil {
		return err
	}
	if err = addClientUserAgent(stack, options); err != nil {
		return err
	}
	if err = smithyhttp.AddErrorCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = smithyhttp.AddCloseResponseBodyMiddleware(stack); err != nil {
		return err
	}
	if err = addSetLegacyContextSigningOptionsMiddleware(stack); err != nil {
		return err
	}
	if err = stack.Initialize.Add(newServiceMetadataMiddleware_opCreateMLEndpoint(options.Region), middleware.Before); err != nil {
		return err
	}
	if err = addRecursionDetection(stack); err != nil {
		return err
	}
	if err = addRequestIDRetrieverMiddleware(stack); err != nil {
		return err
	}
	if err = addResponseErrorMiddleware(stack); err != nil {
		return err
	}
	if err = addRequestResponseLogging(stack, options); err != nil {
		return err
	}
	if err = addDisableHTTPSMiddleware(stack, options); err != nil {
		return err
	}
	return nil
}

func newServiceMetadataMiddleware_opCreateMLEndpoint(region string) *awsmiddleware.RegisterServiceMetadata {
	return &awsmiddleware.RegisterServiceMetadata{
		Region:        region,
		ServiceID:     ServiceID,
		OperationName: "CreateMLEndpoint",
	}
}